file_tag = sprintf("%s_BL_%s", cell_type_name, graph_weight)
assayed_genes = scan(sprintf("output/gene_list_%s.txt", file_tag),
what = character(), sep="\n")
gene_sets = scan(sprintf("output/name_s_%s.txt", file_tag),
what = character(), sep="\n")
gene_sets = sapply(gene_sets, strsplit, USE.NAMES=FALSE, split=",")
n_genes = sapply(gene_sets, length)
names(n_genes) = NULL
summary(n_genes)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 16.00 17.00 18.00 17.85 18.00 19.00
## [1] 40
## [1] 16 17 17 17 17 17 17 17 17 17 17 17 18 18 18 18 18 18 18 18 18 18 18 18 18
## [26] 18 18 18 18 18 18 18 18 19 19 19 19 19 19 19
bioMart.All the gene symbols that can be found in bioMart are
consistent with what we have. So no need to run it.
ensembl = useMart("ensembl", dataset = "hsapiens_gene_ensembl")
gene_BM = getBM(attributes = c("hgnc_symbol", "external_gene_name"),
filters = "external_gene_name",
values = assayed_genes,
mart = ensembl)
length(assayed_genes)
dim(gene_BM)
gene_BM[1:2,]
table(assayed_genes %in% gene_BM$external_gene_name)
t1 = table(gene_BM$external_gene_name)
dup = names(t1)[t1 > 1]
gene_BM[gene_BM$external_gene_name %in% dup,]
table(gene_BM$hgnc_symbol == gene_BM$external_gene_name)
w2kp = which(gene_BM$hgnc_symbol != gene_BM$external_gene_name)
gene_BM[w2kp,]alias2Symbol function from
limma.a2s = rep(NA, length(assayed_genes))
for(i in 1:length(assayed_genes)){
gi = assayed_genes[i]
ai = alias2Symbol(gi)
if(length(ai) > 1){
print(gi)
print(ai)
}
a2s[i] = ai[1]
}## [1] "QARS"
## [1] "EPRS1" "QARS1"
## [1] "SEPT2"
## [1] "SEPTIN6" "SEPTIN2"
##
## FALSE TRUE
## 1607 42
##
## FALSE TRUE <NA>
## 42 1565 42
gene_info = data.table(sym_in_data = assayed_genes, sym_limma = a2s)
gene_info[sym_in_data != sym_limma,]## sym_in_data sym_limma
## 1: C10orf91 LINC02870
## 2: C12orf10 MYG1
## 3: C12orf45 NOPCHAP1
## 4: C6orf48 SNHG32
## 5: C6orf99 LINC02901
## 6: CXorf40A EOLA1
## 7: CXorf57 RADX
## 8: FAM102A EEIG1
## 9: FAM173A ANTKMT
## 10: FAM213B PRXL2B
## 11: H2AFX H2AX
## 12: HIST1H2AG H2AC11
## 13: HIST1H2BK H2BC12
## 14: HIST1H2BN H2BC15
## 15: HIST1H3A H3C1
## 16: HIST1H3H H3C10
## 17: HIST1H4C H4C3
## 18: HIST2H2BF H2BC18
## 19: KIAA0391 PRORP
## 20: QARS EPRS1
## 21: SEPT6 SEPTIN6
## 22: ARNTL BMAL1
## 23: C12orf65 MTRFR
## 24: C16orf72 HAPSTR1
## 25: CCDC84 CENATAC
## 26: DOPEY2 DOP1B
## 27: FAM126B HYCC2
## 28: FAM160B1 FHIP2A
## 29: H1FX H1-10
## 30: H2AFJ H2AJ
## 31: HEXDC HEXD
## 32: HIST1H1C H1-2
## 33: HIST1H1D H1-3
## 34: HIST1H1E H1-4
## 35: KIAA1109 BLTP1
## 36: KIAA1551 RESF1
## 37: MKL1 MRTFA
## 38: NARFL CIAO3
## 39: SEPT2 SEPTIN6
## 40: TARSL2 TARS3
## 41: TMEM8A PGAP6
## 42: WDR60 DYNC2I1
## sym_in_data sym_limma
gene_info[, gene_symbol := sym_in_data]
gene_info[which(sym_in_data != sym_limma), gene_symbol := sym_limma]
dim(gene_info)## [1] 1649 3
## sym_in_data sym_limma gene_symbol
## 1: ABLIM1 ABLIM1 ABLIM1
## 2: AC004687.1 <NA> AC004687.1
## 3: AC004854.2 <NA> AC004854.2
## 4: AC007384.1 <NA> AC007384.1
## 5: AC007952.4 <NA> AC007952.4
## t1
## 1 2
## 1647 1
## sym_in_data sym_limma gene_symbol
## 1: SEPT6 SEPTIN6 SEPTIN6
## 2: SEPT2 SEPTIN6 SEPTIN6
Gene set annotations (by gene symbols) were downloaded from MSigDB website.
gmtfile = list()
gmtfile[["reactome"]] = "../Annotation/c2.cp.reactome.v2023.2.Hs.symbols.gmt"
gmtfile[["go_bp"]] = "../Annotation/c5.go.bp.v2023.2.Hs.symbols.gmt"
gmtfile[["immune"]] = "../Annotation/c7.all.v2023.2.Hs.symbols.gmt"
pathways = list()
for(k1 in names(gmtfile)){
pathways[[k1]] = gmtPathways(gmtfile[[k1]])
}
names(pathways)## [1] "reactome" "go_bp" "immune"
## reactome go_bp immune
## 1692 7647 5219
Filter gene sets for size between 10 and 500.
## $reactome
## 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
## 5.0 7.0 9.0 12.0 17.0 23.0 31.0 44.0 71.8 120.9 1463.0
##
## $go_bp
## 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
## 5.0 6.0 8.0 10.0 14.0 19.0 29.0 46.0 80.8 183.0 1966.0
##
## $immune
## 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
## 5 162 193 197 199 199 200 200 200 200 1992
## [1] 1649 3
max_n2kp = 10
goseq_res = NULL
for(k in 1:length(gene_sets)){
if(length(gene_sets[[k]]) < 10) { next }
print(k)
set_k = paste0("set_", k)
print(gene_sets[[k]])
genes = gene_info$sym_in_data %in% gene_sets[[k]]
names(genes) = gene_info$gene_symbol
table(genes)
pwf = nullp(genes, "hg38", "geneSymbol")
for(k1 in names(pathways)){
p1 = pathways[[k1]]
res1 = goseq(pwf, "hg38", "geneSymbol",
gene2cat=goseq:::reversemapping(p1))
res1$FDR = p.adjust(res1$over_represented_pvalue, method="BH")
nD = sum(res1$FDR < 0.1)
if(nD > 0){
res1 = res1[order(res1$FDR),][1:min(nD, max_n2kp),]
res1$category = gsub("REACTOME_|GOBP_", "", res1$category)
res1$category = gsub("_", " ", res1$category)
res1$category = tolower(res1$category)
res1$category = substr(res1$category, start=1, stop=81)
goseq_res[[set_k]][[k1]] = res1
}
}
}## [1] 1
## [1] "ARHGEF3" "ARL4C" "BROX" "COL6A2" "COL6A3" "DMTF1"
## [7] "ELMOD3" "FAM169A" "GPR174" "IFITM2" "LAIR2" "LINC02256"
## [13] "PIK3CD" "PIK3R5" "RUBCN" "SLCO3A1" "SUSD6" "TRGV10"
## [19] "XCL1"
## [1] 2
## [1] "ISCA1" "LCP2" "NSUN6" "NT5E" "SLC27A5" "TRAT1"
## [7] "AFF1" "AFF4" "COX19" "ITK" "LONP2" "MYO9A"
## [13] "PNPLA8" "TBC1D14" "TRAPPC11" "TRAPPC8" "TRAPPC9" "ZNF557"
## [1] 3
## [1] "CAMK4" "CCNB1IP1" "CMTM7" "EPHX2" "HDHD3" "HIBADH"
## [7] "LBH" "MZT2A" "PCMTD2" "PDE7A" "SNHG15" "TC2N"
## [13] "THEM4" "ZFAS1" "CD46" "FAM126B" "KLF3" "VPS13A"
## [1] 4
## [1] "CREBL2" "DYRK4" "IGKV3-20" "MZF1" "NBPF14" "TBCCD1"
## [7] "TRAV13-1" "TRAV8-3" "TRGV5" "TSPYL4" "CYTOR" "IQCG"
## [13] "PATL2" "PYROXD1" "SENP7" "TRIM38" "TSPAN32" "ZNF683"
## [1] 5
## [1] "CCR7" "TRABD2A" "AC116407.2" "DOCK10" "HRH2"
## [6] "LINC02446" "MX2" "OAS2" "OXNAD1" "PCED1B"
## [11] "S100A12" "TRAV12-3" "TRAV19" "TRAV27" "TRAV4"
## [16] "TRAV9-2" "TRBV11-2" "TRBV4-2"
## [1] 6
## [1] "BBS9" "COG5" "DTHD1" "KLRF1" "LRRC23" "MAP3K2"
## [7] "MTRNR2L8" "NT5C3B" "TOX" "TRAV3" "TRBV7-2" "TRGV8"
## [13] "ZNF862" "COG7" "MCTP2" "MYBL1" "TRGC2"
## [1] 7
## [1] "CST3" "APOL6" "CD226" "DIAPH2" "DOCK11" "EPSTI1" "ERAP2"
## [8] "GNPTAB" "GPR141" "LILRB1" "MIGA1" "OGA" "PARP15" "PTPRJ"
## [15] "ST6GAL1" "TTC17" "UNC13D" "ZNF493"
## [1] 8
## [1] "ARMH1" "BTG1" "IL6R" "SLC2A3" "TMIGD2" "ARHGAP45"
## [7] "DDIT4" "HEXDC" "IL6ST" "ITM2A" "OSM" "PPP4R3B"
## [13] "PSMA3-AS1" "STK17B" "TARSL2" "TENT5C" "Z93930.2" "ZC3H7B"
## [1] 9
## [1] "ALOX5AP" "FCRL3" "GCSAM" "GTF3A" "ICAM3" "MFNG"
## [7] "TRBC1" "ADGRE5" "ARHGAP30" "CCL4" "CD38" "CTSW"
## [13] "FCRL6" "FGFBP2" "SLA2" "TBC1D2B" "TRBC2" "ZAP70"
## [19] "ZNF276"
## [1] 10
## [1] "ANKRD49" "ATAD2B" "CCNH" "CES1" "CLUH" "FAM13B"
## [7] "GPATCH2L" "INO80D" "MICAL2" "MX1" "NAA25" "NARFL"
## [13] "NLRC5" "PARP9" "RHOH" "STAT4" "SYNRG"
## [1] 11
## [1] "AC027644.3" "AC087623.3" "AC119396.1" "AC245297.3" "ARRDC2"
## [6] "IER5" "KLF10" "KMT2E-AS1" "LINC00649" "RAB33B"
## [11] "SDR42E2" "SESN2" "TCP11L2" "WARS2" "MARF1"
## [16] "RUFY2" "SZT2" "XIST"
## [1] 12
## [1] "ASL" "GALNT11" "NXT2" "ASCL2" "BTN3A1" "FRYL" "GNLY"
## [8] "GON4L" "HSH2D" "INPP4A" "PHF14" "POLH" "RALGAPB" "SEMA4D"
## [15] "TAOK1" "TAOK3" "USP16" "ZEB2"
## [1] 13
## [1] "AL118516.1" "AL451085.1" "AL627171.1" "ATP2B1-AS1" "HELQ"
## [6] "INPP4B" "LINC02273" "NUP58" "PRR7" "PTGER4"
## [11] "RGS1" "AC016831.7" "CEMIP2" "CRYBG1" "GDPD5"
## [16] "PRR5L" "THUMPD3-AS1" "TMEM131L"
## [1] 14
## [1] "RELT" "B4GALT1" "CAPNS1" "CROCC" "CST7" "CX3CR1"
## [7] "DDHD1" "IL2RG" "IRAK4" "LINC02384" "MBP" "RNF213"
## [13] "SAMD9L" "SPN" "SYNE1" "UBE2H" "UBR2"
## [1] 15
## [1] "CYB5D2" "INTS6" "INTS8" "PASK" "PITPNC1" "TMEM134" "TRG-AS1"
## [8] "CCDC88C" "EFHD2" "GZMA" "GZMH" "NEAT1" "PEX1" "PEX26"
## [15] "PRR14L" "SSH1" "STK10"
## [1] 16
## [1] "AC004854.2" "AC083798.2" "AK5" "CD40LG" "CITED2"
## [6] "EI24" "FAM213B" "FXYD7" "MYLIP" "NR1D1"
## [11] "PIK3IP1" "PPP1R15B" "RGL4" "SLC38A2" "TESPA1"
## [16] "WDR86" "WSB1" "ARRDC3" "ITPR2"
## [1] 17
## [1] "ABCA5" "AC020659.1" "ADHFE1" "CCDC84" "CLEC16A"
## [6] "CPPED1" "DDX60L" "GABPB2" "GCN1" "HECTD4"
## [11] "ISG20" "LAG3" "ODF3B" "PDZD4" "TMEM127"
## [16] "TRAC" "VTI1A" "ZCCHC2"
## [1] 18
## [1] "AHCTF1" "CAPN15" "CCDC112" "DOPEY2" "H6PD" "HLA-DPB1"
## [7] "HLA-DQA1" "KLHDC4" "N4BP1" "PNPLA6" "PREX1" "PTGDS"
## [13] "RREB1" "SLC38A10" "TBC1D9B" "ZNF292" "ZNF318"
## [1] 19
## [1] "C12orf45" "CLDND1" "CXXC5" "GSTM1" "ITGAE" "KCTD7"
## [7] "KLRK1" "MSC" "NCR1" "PAPSS1" "RHOC" "SESN1"
## [13] "ARAP2" "GALNT3" "HIVEP3" "NLRC3" "SLF2" "ZDHHC5"
## [1] 20
## [1] "HMBOX1" "KIF9" "ABCA7" "ANKRD36" "AP3B1" "AP3M2" "ARHGEF9"
## [8] "C2CD3" "C5orf24" "GPHN" "PIP4K2B" "RIPOR2" "UVRAG" "VPS18"
## [15] "VPS39" "WDR60" "XPO6" "ZBTB20" "ZNF407"
## [1] 21
## [1] "GADD45B" "TRBV6-1" "AKNA" "DENND4B" "FAM78A"
## [6] "GPR132" "HPS4" "MT2A" "NBEAL2" "NUTM2B-AS1"
## [11] "PCNX1" "PUM3" "SEC14L1" "SLC16A1-AS1" "TRANK1"
## [16] "TRBV2" "TRGV4" "TTC38" "ZNF83"
## [1] 22
## [1] "AC044849.1" "APMAP" "C10orf91" "MATK" "BICRAL"
## [6] "ERBIN" "GZMB" "ITGAL" "KIAA2026" "MYO1G"
## [11] "NKG7" "RAP1GAP2" "RASGRP1" "RNF125" "RNF19A"
## [16] "SPON2" "SRGN" "VPS13C"
## [1] 23
## [1] "AMD1" "CCNL1" "GLTP" "NT5DC1" "RGCC" "RSRP1"
## [7] "SERINC5" "SNHG12" "ANKRD36B" "ANKRD36C" "CHD9" "EML4"
## [13] "ENOSF1" "NFATC3" "PARP4" "SLFN12L" "TEP1" "TTC14"
## [19] "ZNF708"
## [1] 24
## [1] "AC008555.5" "AL135791.1" "BTG2" "CXorf40A" "LIME1"
## [6] "LINC00402" "MCUB" "PDCD4-AS1" "PGGHG" "PRAG1"
## [11] "TNFRSF25" "TRAV14DV4" "ZNF749" "CARD16" "GK5"
## [16] "MIAT" "PCSK7" "SPATA13"
## [1] 25
## [1] "CSRNP1" "ID1" "TXK" "ZC3H12A" "ARID5B" "CISH" "EHBP1L1"
## [8] "FGL2" "GBP1" "GBP5" "KLF6" "MKL1" "NFKBIZ" "PIM1"
## [15] "PLAC8" "RIC3" "SETD5"
## [1] 26
## [1] "ABR" "ARAP1" "C16orf72" "CHD6" "CREBZF" "DUS1L"
## [7] "FAM53B" "HECA" "HERC3" "HERC6" "INPP5D" "LY6E"
## [13] "PARP11" "RAB27B" "SYTL3" "TTC16" "XAF1" "ZNF652"
## [1] 27
## [1] "CD27" "CD28" "COA1" "COQ8A" "CRLF3" "CYB561A3"
## [7] "GZMK" "IER3" "KLRG1" "LEPROTL1" "RCSD1" "RTRAF"
## [13] "SLC38A1" "STK17A" "TMEM107" "TMEM42" "ZFAND1" "RFWD3"
## [1] 28
## [1] "AIF1" "ANXA2R" "BEX4" "CHRM3-AS2" "EPS8" "RCAN3"
## [7] "SELL" "TCEA3" "CASP10" "CHD1" "CYTH1" "MIDN"
## [13] "MSI2" "RNF157" "SCRN3" "SOS1" "VCAN"
## [1] 29
## [1] "AOAH" "CARHSP1" "EOMES" "GIMAP1" "GSTM4" "ADGRG1"
## [7] "DGKD" "IGKV3-15" "IRF9" "ITGAM" "KIR2DL3" "MYO1F"
## [13] "NCKAP1L" "NECAP1" "PRKCH" "SLFN5" "TUT7" "YPEL1"
## [1] 30
## [1] "AC007384.1" "AC015982.1" "CCL4L2" "MZF1-AS1" "RETREG1"
## [6] "ABCC10" "AC092683.1" "AP005482.1" "BMT2" "FAM133B"
## [11] "GRK2" "MINDY2" "POLR2J3-1" "SIDT1" "THAP5"
## [16] "TRDC" "TRDV1" "XCL2" "ZNF808"
## [1] 31
## [1] "AC004687.1" "AC007952.4" "AC025164.1" "AC025171.3" "AC087239.1"
## [6] "AC245014.3" "AL121944.1" "AL139246.5" "CRTAM" "ILF3-DT"
## [11] "JAML" "NR4A3" "SNHG8" "SNHG9" "TRAV12-2"
## [16] "TRBV3-1" "TRBV6-2" "TRBV7-9"
## [1] 32
## [1] "ADCY7" "BCL9L" "CELF2" "CHST12" "ETNK1" "GALNT2"
## [7] "KCNAB2" "KIAA1109" "KIAA1551" "KLF2" "MPPE1" "PLEK"
## [13] "PRDM2" "PTPN7" "SUSD1" "UGGT1" "WDTC1" "ZBP1"
## [1] 33
## [1] "CD84" "CMC1" "FAM118A" "GLA" "HIKESHI"
## [6] "HLA-DMB" "KIR3DL2" "KLRC3" "LETMD1" "MAPRE2"
## [11] "SH2D1A" "TRAV38-2DV8" "TRBV6-5" "TRGV9" "MCOLN2"
## [16] "TMEM181"
## [1] 34
## [1] "GATA3" "GPR183" "MAP3K8" "NR4A2" "SLC4A4" "TIGIT"
## [7] "ARHGAP10" "CSNK1G2" "FAM160B1" "GPRIN3" "LPCAT1" "LRRC8A"
## [13] "PARP14" "RAPGEF1" "SLC20A1" "TBX21" "TGFBR3" "ZFAND3"
## [1] 35
## [1] "ALKBH7" "ARL4A" "ATP5F1A" "C6orf48" "EFCAB2" "FAM173A" "FCMR"
## [8] "MPST" "NOSIP" "PTRHD1" "RGS10" "ELMO1" "IQGAP2" "LPIN1"
## [15] "PDE4B" "PDE4D" "TOB1" "TUT4"
## [1] 36
## [1] "AC012645.3" "AC016405.3" "AC020911.2" "AC083880.1" "AC091271.1"
## [6] "AC103591.3" "AF213884.3" "AL357060.1" "ARF4-AS1" "C6orf99"
## [11] "CSKMT" "HIPK1-AS1" "INTS6L" "KCNQ1OT1" "LINC01465"
## [16] "NPIPB4" "OSER1-DT" "Z93241.1"
## [1] 37
## [1] "BNIP3L" "MXI1" "NUAK2" "PDE3B" "GALNT10" "HIPK1" "IFI44L"
## [8] "MBD5" "NRDC" "PPM1K" "RASA3" "RLF" "SETX" "TMEM8A"
## [15] "TRBV7-6" "VPS13B" "VPS13D"
## [1] 38
## [1] "AL138963.3" "IGLV1-44" "LRRN3" "LST1" "MATR3-1"
## [6] "NOCT" "THAP9-AS1" "TRAV1-2" "TRAV21" "TRAV5"
## [11] "TRAV8-4" "TRBV20-1" "TRBV28" "TRBV9" "TRGV7"
## [16] "VAMP7" "IFI27"
## [1] 39
## [1] "C12orf10" "COQ7" "CXorf57" "EPB41L4A-AS1" "FAM102A"
## [6] "HIST1H3H" "IFRD1" "LDLRAP1" "LTB" "NELL2"
## [11] "TCF7" "TMEM204" "ZNF10" "ZNF575" "MAPK8IP3"
## [16] "USP34" "ZBTB40"
## [1] 40
## [1] "AL136454.1" "BX284668.6" "TRAV8-2" "DDX3Y" "EIF1AY"
## [6] "ETFDH" "KDM5D" "MAF" "MTERF2" "RPAP1"
## [11] "RPS4Y1" "SBNO2" "TRAV17" "TTTY15" "UTY"
## [16] "ZMIZ2" "ZNF236"
for(n1 in names(goseq_res)){
k = as.numeric(gsub("set_", "", n1))
print(n1)
print(gene_sets[[k]])
print(goseq_res[[n1]])
}## [1] "set_1"
## [1] "ARHGEF3" "ARL4C" "BROX" "COL6A2" "COL6A3" "DMTF1"
## [7] "ELMOD3" "FAM169A" "GPR174" "IFITM2" "LAIR2" "LINC02256"
## [13] "PIK3CD" "PIK3R5" "RUBCN" "SLCO3A1" "SUSD6" "TRGV10"
## [19] "XCL1"
## $reactome
## category
## 159 collagen biosynthesis and modifying enzymes
## 160 collagen chain trimerization
## 590 ncam1 interactions
## 72 assembly of collagen fibrils and other multimeric structures
## 162 collagen formation
## over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 159 9.873335e-05 1.0000000 2 2
## 160 9.873335e-05 1.0000000 2 2
## 590 2.945125e-04 0.9999992 2 3
## 72 2.946069e-04 0.9999992 2 3
## 162 2.946069e-04 0.9999992 2 3
## FDR
## 159 0.05741344
## 160 0.05741344
## 590 0.06852556
## 72 0.06852556
## 162 0.06852556
##
## [1] "set_2"
## [1] "ISCA1" "LCP2" "NSUN6" "NT5E" "SLC27A5" "TRAT1"
## [7] "AFF1" "AFF4" "COX19" "ITK" "LONP2" "MYO9A"
## [13] "PNPLA8" "TBC1D14" "TRAPPC11" "TRAPPC8" "TRAPPC9" "ZNF557"
## $reactome
## category over_represented_pvalue
## 748 rab regulation of trafficking 4.358593e-05
## under_represented_pvalue numDEInCat numInCat FDR
## 748 0.9999989 4 15 0.05069043
##
## $go_bp
## category over_represented_pvalue under_represented_pvalue
## 4649 vesicle coating 5.212310e-06 1.0000000
## 4658 vesicle targeting 1.293776e-05 0.9999999
## 4661 vesicle tethering 1.293776e-05 0.9999999
## numDEInCat numInCat FDR
## 4649 3 4 0.02023034
## 4658 3 5 0.02023034
## 4661 3 5 0.02023034
##
## [1] "set_8"
## [1] "ARMH1" "BTG1" "IL6R" "SLC2A3" "TMIGD2" "ARHGAP45"
## [7] "DDIT4" "HEXDC" "IL6ST" "ITM2A" "OSM" "PPP4R3B"
## [13] "PSMA3-AS1" "STK17B" "TARSL2" "TENT5C" "Z93930.2" "ZC3H7B"
## $reactome
## category over_represented_pvalue
## 478 interleukin 6 family signaling 1.531729e-05
## under_represented_pvalue numDEInCat numInCat FDR
## 478 0.9999999 3 8 0.01781401
##
## [1] "set_9"
## [1] "ALOX5AP" "FCRL3" "GCSAM" "GTF3A" "ICAM3" "MFNG"
## [7] "TRBC1" "ADGRE5" "ARHGAP30" "CCL4" "CD38" "CTSW"
## [13] "FCRL6" "FGFBP2" "SLA2" "TBC1D2B" "TRBC2" "ZAP70"
## [19] "ZNF276"
## $go_bp
## category
## 135 antigen receptor mediated signaling pathway
## 1132 immune response regulating cell surface receptor signaling pathway
## over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 135 1.435375e-06 0.9999999 7 62
## 1132 1.060749e-05 0.9999994 7 83
## FDR
## 135 0.006733346
## 1132 0.024879875
##
## [1] "set_20"
## [1] "HMBOX1" "KIF9" "ABCA7" "ANKRD36" "AP3B1" "AP3M2" "ARHGEF9"
## [8] "C2CD3" "C5orf24" "GPHN" "PIP4K2B" "RIPOR2" "UVRAG" "VPS18"
## [15] "VPS39" "WDR60" "XPO6" "ZBTB20" "ZNF407"
## $reactome
## category over_represented_pvalue
## 895 sars cov 2 modulates autophagy 1.133752e-06
## under_represented_pvalue numDEInCat numInCat FDR
## 895 1 3 3 0.001318553
##
## $go_bp
## category over_represented_pvalue
## 4354 snare complex assembly 1.330716e-06
## 4657 vesicle organization 2.016482e-06
## 2256 organelle membrane fusion 8.249263e-06
## 2254 organelle fusion 2.042630e-05
## 1423 membrane fusion 2.072087e-05
## 4454 synaptic vesicle cytoskeletal transport 1.298258e-04
## 3894 regulation of snare complex assembly 1.337203e-04
## under_represented_pvalue numDEInCat numInCat FDR
## 4354 1.0000000 3 3 0.004729658
## 4657 0.9999999 6 38 0.004729658
## 2256 0.9999999 4 13 0.012899098
## 2254 0.9999996 4 16 0.019440325
## 1423 0.9999996 4 16 0.019440325
## 4454 1.0000000 2 2 0.089611692
## 3894 1.0000000 2 2 0.089611692
##
## [1] "set_22"
## [1] "AC044849.1" "APMAP" "C10orf91" "MATK" "BICRAL"
## [6] "ERBIN" "GZMB" "ITGAL" "KIAA2026" "MYO1G"
## [11] "NKG7" "RAP1GAP2" "RASGRP1" "RNF125" "RNF19A"
## [16] "SPON2" "SRGN" "VPS13C"
## $reactome
## category over_represented_pvalue under_represented_pvalue numDEInCat
## 754 rap1 signalling 6.075026e-05 1 2
## numInCat FDR
## 754 2 0.07065255
##
## $immune
## category over_represented_pvalue
## 2392 gse26495 naive vs pd1low cd8 tcell dn 8.615551e-06
## under_represented_pvalue numDEInCat numInCat FDR
## 2392 0.9999995 7 77 0.04392208
##
## [1] "set_25"
## [1] "CSRNP1" "ID1" "TXK" "ZC3H12A" "ARID5B" "CISH" "EHBP1L1"
## [8] "FGL2" "GBP1" "GBP5" "KLF6" "MKL1" "NFKBIZ" "PIM1"
## [15] "PLAC8" "RIC3" "SETD5"
## $immune
## category
## 20 fletcher pbmc bcg 10w infant ppd stimulated vs unstimulated 10w up
## 3583 gse3920 untreated vs ifna treated fibroblast up
## 3339 gse36888 untreated vs il2 treated tcell 6h up
## 4891 gse9988 anti trem1 vs anti trem1 and lps monocyte dn
## 4888 gse9988 anti trem1 and lps vs ctrl treated monocytes up
## 2916 gse30971 wbp7 het vs ko macrophage dn
## 5090 van den biggelaar pbmc prevnar 9mo infant stimulated vs unstimulated 9mo up
## 2909 gse30971 ctrl vs lps stim macrophage wbp7 ko 2h up
## 2912 gse30971 wbp7 het vs ko macrophage 2h lps stim dn
## 2911 gse30971 ctrl vs lps stim macrophage wbp7 ko 4h up
## over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 20 9.958736e-06 0.9999998 4 14
## 3583 2.558259e-05 0.9999990 5 36
## 3339 3.201994e-05 0.9999986 5 37
## 4891 4.379491e-05 0.9999980 5 36
## 4888 6.422389e-05 0.9999968 5 41
## 2916 7.157358e-05 0.9999978 4 21
## 5090 9.112306e-05 0.9999987 3 9
## 2909 1.055383e-04 0.9999963 4 23
## 2912 1.303632e-04 0.9999951 4 25
## 2911 1.346986e-04 0.9999949 4 24
## FDR
## 20 0.05076964
## 3583 0.05441255
## 3339 0.05441255
## 4891 0.05581662
## 4888 0.06081368
## 2916 0.06081368
## 5090 0.06636363
## 2909 0.06725426
## 2912 0.06767447
## 2911 0.06767447
##
## [1] "set_29"
## [1] "AOAH" "CARHSP1" "EOMES" "GIMAP1" "GSTM4" "ADGRG1"
## [7] "DGKD" "IGKV3-15" "IRF9" "ITGAM" "KIR2DL3" "MYO1F"
## [13] "NCKAP1L" "NECAP1" "PRKCH" "SLFN5" "TUT7" "YPEL1"
## $go_bp
## category over_represented_pvalue
## 3048 protein kinase c signaling 1.463583e-05
## under_represented_pvalue numDEInCat numInCat FDR
## 3048 0.9999999 3 6 0.06865668
##
## [1] "set_31"
## [1] "AC004687.1" "AC007952.4" "AC025164.1" "AC025171.3" "AC087239.1"
## [6] "AC245014.3" "AL121944.1" "AL139246.5" "CRTAM" "ILF3-DT"
## [11] "JAML" "NR4A3" "SNHG8" "SNHG9" "TRAV12-2"
## [16] "TRBV3-1" "TRBV6-2" "TRBV7-9"
## $go_bp
## category
## 1083 heterophilic cell cell adhesion via plasma membrane cell adhesion molecules
## over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 1083 2.059281e-05 1 2 4
## FDR
## 1083 0.09660088
##
## [1] "set_34"
## [1] "GATA3" "GPR183" "MAP3K8" "NR4A2" "SLC4A4" "TIGIT"
## [7] "ARHGAP10" "CSNK1G2" "FAM160B1" "GPRIN3" "LPCAT1" "LRRC8A"
## [13] "PARP14" "RAPGEF1" "SLC20A1" "TBX21" "TGFBR3" "ZFAND3"
## $immune
## category
## 4407 gse5542 untreated vs ifna treated epithelial cells 6h up
## over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 4407 1.614583e-05 0.9999991 6 51
## FDR
## 4407 0.08231146
##
## [1] "set_40"
## [1] "AL136454.1" "BX284668.6" "TRAV8-2" "DDX3Y" "EIF1AY"
## [6] "ETFDH" "KDM5D" "MAF" "MTERF2" "RPAP1"
## [11] "RPS4Y1" "SBNO2" "TRAV17" "TTTY15" "UTY"
## [16] "ZMIZ2" "ZNF236"
## $immune
## category
## 4352 gse5099 classical m1 vs alternative m2 macrophage dn
## over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 4352 1.958376e-05 0.9999996 4 20
## FDR
## 4352 0.09983799
## used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
## Ncells 8958343 478.5 16391124 875.4 NA 16391124 875.4
## Vcells 19140580 146.1 59907924 457.1 65536 77218972 589.2
## R version 4.2.3 (2023-03-15)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Ventura 13.4.1
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] TxDb.Hsapiens.UCSC.hg38.knownGene_3.16.0
## [2] GenomicFeatures_1.50.4
## [3] GenomicRanges_1.50.2
## [4] GenomeInfoDb_1.34.9
## [5] org.Hs.eg.db_3.16.0
## [6] AnnotationDbi_1.60.2
## [7] IRanges_2.32.0
## [8] S4Vectors_0.36.2
## [9] Biobase_2.58.0
## [10] BiocGenerics_0.44.0
## [11] goseq_1.50.0
## [12] geneLenDataBase_1.34.0
## [13] BiasedUrn_2.0.10
## [14] fgsea_1.24.0
## [15] biomaRt_2.54.1
## [16] limma_3.54.2
## [17] tidyr_1.3.0
## [18] ggpubr_0.6.0
## [19] ggplot2_3.4.2
## [20] data.table_1.14.8
##
## loaded via a namespace (and not attached):
## [1] nlme_3.1-162 matrixStats_1.0.0
## [3] bitops_1.0-7 bit64_4.0.5
## [5] filelock_1.0.2 progress_1.2.2
## [7] httr_1.4.6 tools_4.2.3
## [9] backports_1.4.1 bslib_0.4.2
## [11] utf8_1.2.3 R6_2.5.1
## [13] mgcv_1.8-42 DBI_1.1.3
## [15] colorspace_2.1-0 withr_2.5.0
## [17] tidyselect_1.2.0 prettyunits_1.1.1
## [19] bit_4.0.5 curl_5.0.1
## [21] compiler_4.2.3 cli_3.6.1
## [23] xml2_1.3.4 DelayedArray_0.24.0
## [25] rtracklayer_1.58.0 sass_0.4.5
## [27] scales_1.2.1 rappdirs_0.3.3
## [29] Rsamtools_2.14.0 stringr_1.5.0
## [31] digest_0.6.31 rmarkdown_2.21
## [33] XVector_0.38.0 pkgconfig_2.0.3
## [35] htmltools_0.5.5 MatrixGenerics_1.10.0
## [37] dbplyr_2.3.2 fastmap_1.1.1
## [39] rlang_1.1.0 rstudioapi_0.14
## [41] RSQLite_2.3.1 BiocIO_1.8.0
## [43] jquerylib_0.1.4 generics_0.1.3
## [45] jsonlite_1.8.4 BiocParallel_1.32.6
## [47] dplyr_1.1.2 car_3.1-2
## [49] RCurl_1.98-1.12 magrittr_2.0.3
## [51] GO.db_3.16.0 GenomeInfoDbData_1.2.9
## [53] Matrix_1.6-4 Rcpp_1.0.10
## [55] munsell_0.5.0 fansi_1.0.4
## [57] abind_1.4-5 lifecycle_1.0.3
## [59] stringi_1.7.12 yaml_2.3.7
## [61] carData_3.0-5 SummarizedExperiment_1.28.0
## [63] zlibbioc_1.44.0 BiocFileCache_2.6.1
## [65] grid_4.2.3 blob_1.2.4
## [67] parallel_4.2.3 crayon_1.5.2
## [69] lattice_0.20-45 splines_4.2.3
## [71] Biostrings_2.66.0 cowplot_1.1.1
## [73] hms_1.1.3 KEGGREST_1.38.0
## [75] knitr_1.44 pillar_1.9.0
## [77] rjson_0.2.21 ggsignif_0.6.4
## [79] codetools_0.2-19 fastmatch_1.1-3
## [81] XML_3.99-0.14 glue_1.6.2
## [83] evaluate_0.20 png_0.1-8
## [85] vctrs_0.6.2 gtable_0.3.3
## [87] purrr_1.0.1 cachem_1.0.7
## [89] xfun_0.39 broom_1.0.4
## [91] restfulr_0.0.15 rstatix_0.7.2
## [93] tibble_3.2.1 GenomicAlignments_1.34.1
## [95] memoise_2.0.1